Many SISR methods have been studied long before, such as bicubic interpolation and Lanczos resampling [1]} which are based on interpolation. However, SISR is an inherently ill-posed problem, and there always exist multiple HR images corresponding to one original LR image. To solve this issue, some numerical methods utilize prior information to restrict the solution space of the reconstruction, such as edge-based methods [2]} and image statistics-based methods [3]}. Meanwhile, there are some widely used learning methods, such as neighbor embedding methods [4]} and sparse coding methods [5]}, which assume that there exists a transformation between LR and HR patches.
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